Search

This paper seeks to optimise fleet management for companies that utilise both internal combustion engine vehicles (ICEVs) and electric vehicles by considering various costs, including fixed costs, variable costs, time window penalty costs, fuel costs, and electricity consumption costs. Additionally, the study examines the influence of four types of regulations, i.e. carbon cap, carbon tax, carbon trading, and carbon offsetting, on carbon emissions and fleet configuration. The optimisation model was solved using a Clarke-Wright savings heuristic algorithm followed by an improved adaptive genetic algorithm (IAGA), and a sensitivity analysis was conducted under different regulatory policies. The results show that all four types of regulations can effectively reduce fleet emissions. While carbon prices have a greater impact on carbon regulations than carbon quota, carbon trading was more effective under similar circumstances. Therefore, governments should implement appropriate regulatory strategies to reduce energy consumption and encourage enterprises to reduce their emissions. [ABSTRACT FROM AUTHOR]

The tetrahedral amorphous carbon (ta-C) coatings are deposited on piston rings to improve the tribological property of the piston ring-cylinder liner system of the internal combustion engines. The deposition parameters are optimized by molecular dynamics simulation to reduce the cost of coatings' fabrication. The ta-C coatings with higher sp3 fraction, lower friction coefficient, and superior anti-wear properties are achieved by optimizing the incident energy and substrate temperature of carbon atoms. The second nearest-neighbor modified embedded-atom method potential and Tersoff potential are used to describe the interatomic interactions. The effects of the incident energy of the carbon atoms and substrate temperature on the deposition properties of the ta-C coatings are discussed. The numerical results show that the ta-C coatings with high sp3 fraction, high density, and good interface mixing are obtained, and the deposition properties of the ta-C coatings are improved. [ABSTRACT FROM AUTHOR]

We present a dynamic perspective to quantify the air quality–related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality– related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits. [ABSTRACT FROM AUTHOR]

The objective of the research is to develop a new methodology capable of quantifying the emissions of internal combustion engine cars based not only on their technology but also on the dynamic behavior of the individual vehicle. No complicated exhaust measurement apparatus is needed. Employing just a telematic device equipped with GNSS and an inertial measurement unit, which can be easily attached to the vehicle, we demonstrate how individualised, accurate climate-altering emissions result by using figures extracted from European test databases, appropriately combined with real travelled distances, speeds, and driving style of each individual car. Pollutant emissions are, in this paper, also assessed though in a more general manner, and this represents a starting point for a future complete vehicle-centric emissions evaluation. This research demonstrates that circulating car emissions have to be assessed considering not only the Euro class and type of fuel, but also how the vehicle is driven. In this work a new, implementation oriented methodology is proposed in order to properly merge average European standard emission data with car-based telematic measures to highlight a new paradigm for regulating in a more conscious way the transition of the internal combustion engine car park towards a large scale, sustainable mobility ecosystem. This approach would place greater responsibility on the driver, without leaving anyone behind and without compelling the car scrapping solely based on the Euro class of its engine. The key contribution is ultimately to establish an easy to handle methodology enabling targeted and behavior-based traffic management policies. In fact, through a massive telematics recent dataset, the proposed virtual emission sensing system reveals that an extensive and inefficient use of eco-friendly vehicles produces much more greenhouse gas emissions than older vehicles driven in an environmentally responsible way. [ABSTRACT FROM AUTHOR]

This study proposes a novel instrument for measuring private car owners’ travel-related lifestyle (PCTRL) based on a survey (N = 2045) conducted in China’s four first-tier cities and ten quasi first-tier cities. By employing principal component analysis (PCA) and cluster analysis, the study classifies electric vhehicle (EV) owners and internal combustion engine vehicle (ICEV) owners into five distinct PCTRL segments, respectively. The findings reveal that only 66% of EV owners have similar PCTRLs to 67% of ICEV owners, with the most notable disparity being the higher likelihood of EV owners choosing private cars for their daily commutes. Furthermore, a random forest model was developed to predict the daily activity-based travel mode choices behavior of both EV and ICEV owners. The findings offer valuable insights into understanding the behavior of EV and ICEV owners in their daily travel mode choices and help formulating more effective traffic management strategies. [ABSTRACT FROM AUTHOR]

For hydrogen internal combustion engines (H 2 ICEs), the existing researches mainly focus on their thermodynamic aspects, while the engine acoustics are paid less attention. The objective of this research is to investigate the combustion noise characteristics of H 2 ICEs and find the biggest lever for combustion noise mitigation. Based on the data from previous thermodynamic measurements of various H 2 ICEs, the influences of different parameters for the combustion noise and knocking are studied with sensitivity analysis and machine learning based method. The results show that increasing Air–fuel equivalence ratio (λ), ignition delay and exhaust-gas recirculation rate (EGR) are acoustically beneficial, where λ is the most effective one with possible noise reduction up to 20 dB. Further, the comparison results between the H 2 ICEs and conventional engines indicates that the combustion noise of the H 2 ICE is kept at similar level as the respective gasoline variant if the H 2 ICE is operated withλ >2. [ABSTRACT FROM AUTHOR]

It has been widely suggested that the transition to battery electric vehicles will require 30% fewer assembly workers than those needed for internal combustion engine vehicles. Here, we use publicly available datasets on vehicle production and employment to show that labor intensity has increased at U.S. vehicle assembly plants that have fully transitioned to assembling battery electric vehicles. During the production ramp-up period, labor intensity increases by more than ten-fold compared to historic combustion vehicle assembly labor intensity. For one assembly site studied, labor intensity and total employment remained three times higher after a decade of electric vehicle production. Our study suggests that it may take longer than 15 years for electric vehicle assembly sites to achieve labor intensity parity with internal combustion vehicle assembly. Thus, rapid widespread loss of employment at vehicle assembly plants is a smaller risk than many fear. Moreover, our study calls for more regionally focused analyses of the transition's effects on labor using data-driven and macro-level surveying approaches. This study finds that U.S. vehicle assembly plants that have fully transitioned from gas engine to electric vehicle assembly have required higher labor intensity. It suggests that more, not fewer, workers are needed for electric vehicle assembly. [ABSTRACT FROM AUTHOR]

Regulations concerning the environmental impact and energy efficiency of ships are becoming increasingly stringent. To meet these demanding criteria, new technologies are actively being developed to achieve emission reductions while maintaining efficient fuel energy conversion into propulsion power. However, the propulsion system behaviour in a dynamic environment of the actual sea is highly nonlinear and complex, and a profound understanding of the mutual interactions is still lacking. This paper proposes an integrated approach for comprehensive propulsion system analysis. The key feature of this technique is the utilisation of an intelligent propeller drive controlled by a marine diesel engine simulator (MDES) to drive the free-running model of a ship, providing real-like behaviour of the engine model in real-time in response to actual measured values. The core of the MDES consists of a continuous cycle-mean value dynamic engine model supplemented with a detailed combustion cycle evaluation. The developed fast calculation algorithm of crank-angle resolved thermodynamic equations of the gas state in the engine cylinder enables the complete engine model to be integrated into the real-time environment of a physical model ship. Thus, the propulsion system's performance can be analysed under conditions that closely mimic those of the actual sea environment. [ABSTRACT FROM AUTHOR]

Internal combustion engines fueled with mixtures of hydrogen (H 2) and ammonia (NH 3) are potential power devices for reducing carbon emissions. To improve the ignition and combustion performance of NH 3 /H 2 , turbulent jet ignition (TJI) can be used. This study aims to investigate NH 3 /H 2 /air combustion under TJI modes at low equivalence ratios. Considering that the adoption of the scavenging system is beneficial for improving the reactivity of the pre-chamber, the effect of active TJI with scavenging is also explored. The results show that injecting 1.2 times the initial mixture volume of air is optimal for scavenging, and the scavenging effect becomes significant as the NH 3 fraction increases. Using conventional active TJI and active TJI with scavenging effectively improves ignition performance and flame propagation, reducing sensitivity to the equivalence ratio compared to passive TJI mode. Although the adoption of active TJI modes improves the lean flammability limit of NH 3 /H 2 , weak flame propagation may occur in the early stage of combustion under ultra-lean conditions. Appropriately increasing the injection of auxiliary H 2 can effectively improve this phenomenon. • Scavenging in the pre-chamber is conducive to the improvement of jet generation. • H 2 -assisted pre-chamber reduces the sensitivity of combustion to equivalence ratio. • Weak flame propagation may occur in the early combustion of ultra-lean mixtures. • An appropriate increase of H 2 injection can improve the initial flame propagation. [ABSTRACT FROM AUTHOR]

For a rapid transition to a carbon-neutral transport sector, hydrogen internal combustion engines could be one measure. To support the development, suitable simulation models are needed. This paper provides enhancements to an existing combustion modeling approach for lean homogeneous hydrogen–air mixtures with online reaction kinetics and combines swirl charge motion with a spark ignited combustion process. These include a real gas equation of state, a wall heat loss model that is suitable for hydrogen and a flow model. The model is implemented in Python using Cantera with a custom solver interface. The model was successfully validated through experimental measurement data from an engine test bench. Additionally, some insights into the validity of the model assumptions are given by comparing model results to three-dimensional computational fluid dynamics simulation data. • Model for a spark-ignited combustion process and swirl-based charge motion. • Solver interface for connection of thermodynamics handled by Cantera and flow model. • Successful model validation using experimental data. • Analysis of flame sphericity with 3D CFD simulation results. [ABSTRACT FROM AUTHOR]

The hydrogen internal combustion engine (H 2 -ICE) is proposed as a robust and viable solution to decarbonise the heavy-duty on- and off-road, as well as the light-duty automotive, sectors of the transportation markets and is therefore the subject of rapidly growing research interest. With the potential for engine performance improvement by controlling the internal mixture formation and avoiding combustion anomalies, hydrogen direct injection (H 2 DI) is a promising combustion mode. Furthermore, the H 2 -ICE poses an attractive proposition for original equipment manufacturers (OEMs) and their suppliers since the fundamental base engine design, components, and manufacturing processes are largely unchanged. Nevertheless, to deliver the highest thermal efficiency and zero-harm levels of tailpipe emissions, moderate adaptations are needed to the engine control, air path, fuel injection, and ignition systems. Therefore, in this article, critical design features, fuel-air mixing, combustion regimes, and exhaust after-treatment systems (EATS) for H 2 DI engines are carefully assessed. [Display omitted] • Key design aspects for achieving high efficiency and low emissions summarised. • Injection and intake ports are critical for good in-cylinder mixture formation. • Thermal management is required to mitigate abnormal combustion. • Advanced boosting system required to obtain high power density. [ABSTRACT FROM AUTHOR]

ABSTRACT The urgency to combat climate change has led countries worldwide to embrace clean energy solutions across various sectors, including transportation, to reduce greenhouse gas emissions. This shift is evident in the growing popularity and adoption of alternative fuel vehicles (AFVs), such as natural gas vehicles and electric vehicles. AFVs have significantly lower carbon footprints compared to conventional petrol‐powered vehicles with internal combustion engines. Consequently, there arises a need to gain a deeper understanding of AFV refueling demand to optimize the distribution of refueling stations. To address this, our research proposes an innovative space–time method that integrates GPS trajectory data with the support vector machine technique to accurately identify and analyze patterns in AFV refueling behavior. The results highlight distinct space–time patterns, notably the clustering of refueling activities in areas like Shuiguohu, Shouyilu, Houhu, Hanshuiqiao, Zhoutou, and Yongfeng around noon, influenced by taxi drivers' breaks. This underscores the importance of increasing staff levels at refueling stations in these areas during peak refueling periods, forming alliances with local eateries, and coordinating taxi shift hours to evenly distribute refueling demand throughout the day, ultimately reducing congestion during peak refueling periods in these areas. The proposed method by this research is applicable to urban contexts worldwide and equips policymakers and planners with a powerful tool for effective planning of future AFV refueling stations. [ABSTRACT FROM AUTHOR]

AbstractThis study focuses on developing an innovative device for isolating and managing exhaust gases from diesel locomotive engines, specifically aiming to reduce environmental impact and enhance operational safety. The study used experimental analysis, validated results using Cochrane and Fisher criteria, and conducted empirical data analysis. Study utilized an experimental stand with a 1.9-liter Volkswagen diesel engine, ZIL-130 compressor, custom exhaust gas storage system with tanks, thermometers, pressure gauges, and control valves. The study developed a mathematical model analysing input parameters and system outputs, achieving 95% accuracy, proving its reliability in representing exhaust gas dynamics of TEM2 diesel locomotives. [ABSTRACT FROM AUTHOR]

With the increasing depletion of fossil fuels, hydrogen has attracted much attention as one of the promising alternative energy sources. However, the large-scale application of hydrogen energy still has many challenges, such as insufficient storage, transportation, and demand. Among the various hydrogen storage media, methylcyclohexane (MCH) is regarded as a potential hydrogen storage technology, because of its unique and excellent safety performance, hydrogen storage capacity, physical and chemical properties, and other notable characteristics. Herein, the paper focuses on the current research progress of dehydrogenation technology, which is discussed in term of the reaction mechanism of MCH dehydrogenation, the research progress of catalysts, and the optimization of process conditions, respectively. Subsequently, a summary is provided to point out the possible reaction network diagrams. Additionally, based on the challenges associated with sourcing heat for applications, we propose a novel dual internal combustion engine drive method for hydrogen production from MCH, this innovative approach is expected to propel the advancement and application of hydrogen energy technology. Then, this work concludes with a brief overview of the current research progress in hydrogenation technology. Finally, it summarizes the present challenges of MCH dehydrogenation, and further research of MCH dehydrogenation have prospected in terms of optimal design theory, preparation of novel catalysts, reduction of energy consumption, reactor enhancement, and system coupling. [Display omitted] • The reaction mechanism of MCH dehydrogenation is explored and analyzed. • A network diagram of possible MCH dehydrogenation reactions is summarized. • Progress in the research of active centers, additives, and supports of the catalysts is discussed. • A novel dual internal combustion engine drive method for hydrogen production from MCH is proposed. • The developments, challenges, and prospects for MCH dehydrogenation are reviewed. [ABSTRACT FROM AUTHOR]

Ammonia is a promising carbon-free fuel for internal combustion engines, but its combustion properties are very poor if compared with conventional fuels. Thus, hydrogen enrichment can be the proper solution in order to overtake the issues related to neat ammonia fueling. In this paper, the authors use a 3D numerical model coupled with a chemical kinetic approach to assess the operation of a light-duty spark-ignition engine fueled by neat ammonia and ammonia-hydrogen blends (up to 15% of hydrogen by volume). The proposed model reproduces the analyzed experimental operating points with a good accuracy. As example, considering the in-cylinder pressure peak, the difference between the calculated maximum pressure and the mean measured one ranges between 1.6% and 6.8% for the examined cases. The 3D approach enables an in-depth analysis of flame development that also allows to detect the effect of hydrogen enrichment on both combustion development and emissions. Unburned ammonia trends are captured, reproducing the measured decrease of ammonia emissions for increasing hydrogen enrichment. The emissions of NO x are also well reproduced. Simulations also highlighted that dissociation of ammonia produces H 2 , which is detected in the combustion chamber also if neat ammonia is burned and, at least according to the chemical mechanism used, not all the produced hydrogen oxidizes. Only very small quantities of intermediates related to ammonia combustion are calculated at exhaust valve opening, decreasing for an increasing hydrogen content in the fuel mixture. • 3D-CFD modeling and simulation of ammonia and hydrogen-enriched ammonia engines. • In-depth analysis of flame development within the combustion chamber. • The characteristic combustion regime for the analyzed cases has been determined. • Experimental trends of engine emissions are well reproduced by the model. • Assessment of unburned ammonia and intermediates formation and consumption. [ABSTRACT FROM AUTHOR]

Nowadays, emissions from internal combustion engines are a relevant topic of investigation, taking into account the continuous reduction of emission limits imposed by environmental regulatory agencies around the world, obviously as the result of earnest studies that have pointed out the impact on the human health of high levels of contaminants released into the environment. Over recent years, the use of biofuels has contributed to attenuating this environmental issue; however, new problems have been raised, such as NOx emissions tend to increase as the biofuel percentage in the fuel used in engines increases. In this research, the emissions of a compression ignition internal combustion engine modeled as a variable volume reactor with homogeneous combustion were numerically investigated. To analyze the combustion process, a detailed kinetics model tailored specifically for this purpose was used. The kinetics model comprised 30,975 chemical reactions involving 691 chemical species. Mixtures of fuel surrogates were then created to represent the fuel used in the Brazilian fuel marketplace, involving (i) fossil diesel—"diesel A", (ii) soybean diesel—"biodiesel", and (iii) hydrotreated vegetable oil— "HVO". Surrogate species were then selected for each of the aforementioned fuels, and blends of those surrogates were then proposed as mixture M1 (diesel A:biodiesel:HVO—90:10:0), mixture M2 (diesel A:biodiesel:HVO—85:15:0), and mixture M3 (diesel A:biodiesel:HVO—80:15:5). The species allowed in the kinetics model included all the fuel surrogates used in this research as well as the target emission species of this study: total hydrocarbons, non-methane hydrocarbons, carbon monoxide, methane, nitrogen oxides, carbon dioxide, soot, and soot precursors. When compared to experimental trends of emissions available in the literature, it was observed that, for all the proposed fuel surrogates blends, the numerical approach performed in this research was able to capture qualitative trends for engine power and the target emissions in the whole ranges of engine speeds and engine loads, despite the CO and NOx emissions at specific engine speeds and loads. [ABSTRACT FROM AUTHOR]

Sequential sampling methods are often used to estimate functions describing models subjected to time‐intensive simulations or expensive experiments. These methods provide guidelines for point selection in the domain to capture maximum information about the function. However, in most sequential sampling methods, determining a new point is a time‐consuming process. In this paper, we propose a new method, named Sieve, to sequentially select points of an initially unknown function based on the definition of proper intervals. In contrast with existing methods, Sieve does not involve function estimation at each iteration. Therefore, it presents a greater computational efficiency for achieving a given accuracy in estimation. Sieve brings in tools from computational geometry to subdivide regions of the domain efficiently. Further, we validate our proposed method through numerical simulations and two case studies on the calibration of internal combustion engines and the optimal exploration of an unknown environment by a mobile robot. [ABSTRACT FROM AUTHOR]

The growing demand of sustainable and environment friendly energy sources has spurred research and development efforts towards the integration of biofuels in various applications, particularly in internal combustion engines. Microemulsion technique is a new and innovative alternative to traditional fossil fuel that has gained a significant attention in recent years. This type of bio fuel is made by blending of small amount of biofuel and large amount of conventional diesel fuel. This review paper explores the potential of enhancing the performance of Compression ignition (CI) engines by incorporating additives into hybrid biofuels. The study focuses on the synergistic effects of combining traditional fossil fuels with bio‐derived components, such as ethanol, biodiesel, and other bio‐based additives. This review paper aim is to explore the performance of a 4‐stroke, single‐cylinder, direct injection Compression Ignition (CI) engine at different loads using different fuels blends like CNWEDB, BFNP150, PPNP150, and ME Diesel/Colza oil. The review outlines recent advancements in biofuel technology, including novel production methods and feedstock options, aiming to overcome limitations associated with conventional biofuels. The article aims to investigate the potential of vegetable oil in formulating MHBF, analyzing its performance and emissions in CI engines. The engine performance parameters viz., brake thermal efficiency brake specific fuel consumption have been reviewed and found that these values are comparable to the biodiesel blends with pure petrodiesel. At 60%, 80%, and full load condition the BTE of microemulsion diesel/colza oil is increasing while at 40%, 80%, and full load the BSFC is decreasing. Emissions reported by the various researchers, however, have a positive attribute with respect to NOx, CO, and UHC. At full load CO is decreasing and at all load conditions the value of UHC is decreasing. The paper concludes with a discussion on future research directions, emphasizing the need for continued innovation to address emerging issues and optimize the performance of CI engines for a sustainable and energy‐efficient future. [ABSTRACT FROM AUTHOR]

Tracer based planar laser-induced fluorescence (PLIF) has emerged as a powerful in-situ measurement technique with a considerable spatial and temporal resolution for Internal combustion (IC) engines. In PLIF, the emitted fluorescence signals from a tracer molecule are processed to determine distribution of temperature, fuel, residual gases, etc. However, it is imperative to have a thorough understanding of the tracer physical properties and its fluorescence intensity dependencies on excitation wavelength, pressure, temperature and bath gas composition existing inside the combustor for accurate quantitative interpretation. This work consists of a series of two articles providing a detailed review of the existing literature of fluorescence characteristics of various molecules used as tracers in IC engine applications. Due to the overwhelming usage of organic compounds in IC engine environment, the work is restricted to them. Part A of this work is focussed on non-aromatic compounds whereas part B will focus on aromatics (toluene, anisole, naphthalene, 1-methylnaphthalene and fluoranthene). Due to a large energy gap between the excited singlet and triplet states of aromatics, they are highly sensitive to oxygen quenching effects than ketones. Absorption cross-section might increase or decrease with temperature but is insensitive to pressure changes. Fluorescence quantum yield of aromatics show a very strong reduction with increase in temperature but might either increase or decrease with increasing pressure. The pressure sensitivity is found to increase with the number of atoms in a bath gas molecule. Fluorescence spectra are found to undergo redshift with temperature which can be used to measure temperature using 2 colour thermometry. The large fluorescence quenching by oxygen can also be used to directly measure fuel–air ratio using FARLIF methodology. Towards the end several IC engine studies are reviewed to discuss various aspects of mixture formation and temperature distribution. [ABSTRACT FROM AUTHOR]

Energy transition and decarbonization present significant challenges to transportation. Electric machines, such as motors and generators, are increasingly replacing internal combustion engines to reduce greenhouse gas emissions. This study focuses on enhancing the energy efficiency of electric machines used in vehicles, which are predominantly powered by batteries with limited energy capacity. By investigating various control strategies, the aim is to minimize energy losses and improve overall vehicle performance. This research examines two types of electric motors: Permanent Magnet Synchronous Motor (PMSM) and Induction Motor (IM). Real-time loss measurements were conducted during simulated driving cycles, including acceleration, constant speed, and braking phases, to mimic typical driving behavior. The simulation utilized characteristics from commercial vehicles, specifically the Renault Zoé and Bombardier eCommander, to assess the controls under different configurations. This study employed the Energetic Macroscopic Representation (EMR) formalism to standardize the analysis across different motors and controls. The results demonstrate significant loss reductions. The controls investigated in this study effectively reduce energy losses in electric motors, supporting their applicability in the automotive industry. [ABSTRACT FROM AUTHOR]

A review of modern scientific literature on the electric double layer capacitors based on the recharging of the electric double layer is presented. The electric double layer capacitors are used in pulse technology devices, as electric energy storage devices, for starter firing, for the recuperating of the braking energy of internal combustion engines, for smoothing peak loads in electric networks, and in various portable devices. The electric double layer capacitors are subdivided into the power electric double layer capacitors and the energy ones. The power (pulse) electric double layer capacitors have a high specific power (up to hundreds of kW/kg), whereas the energy electric double layer capacitors have a high specific energy (~25 W h/kg and higher). Compared to batteries, the power electric double layer capacitors have a much higher power density and better cyclability—up to hundreds of thousands and millions of cycles. Publications on the electric double layer capacitors' self-discharge are reviewed. [ABSTRACT FROM AUTHOR]

The electrification of automotive is growing rapidly, resulting in an increased need for aluminum alloys with high electrical conductivity. The core element of the electric vehicle, besides the batteries, is an electric motor, which replaces the internal combustion engines of a traditional gasoline vehicle. These applications require both high strength and high electrical conductivity. This paper presents the development of a new Al-Fe-Ni aluminum alloy that provides a good combination of mechanical properties and electrical conductivity. The alloy is well suited for high-pressure vacuum die casting (HPVDC). The as-cast microstructures, mechanical properties and electrical conductivity were studied for alloys with different Fe/Ni combination. The relationship between the microstructure and properties is analyzed, and the strengthening mechanisms of the studied alloy are discussed. Based on the experimental results, the new alloy demonstrates excellent potential for electric vehicle applications produced by high-pressure vacuum die casting. [ABSTRACT FROM AUTHOR]

With increasingly stringent emissions regulations, the trend toward using low-carbon fuels in internal combustion engines is unstoppable. Achieving higher rates of methane substitution is a crucial direction for future diesel-methane engines. However, the details of the combustion process involving the auto-ignition of micro pilot diesel fuel and ignition of methane main fuel to form premixed flames are still not clear. Therefore, the study employed visualization technique using a rapid compression machine and numerical study to analyze the process of igniting methane main fuel using various injection strategies for micro pilot diesel fuel. The results indicate that before the onset of the second diesel injection, a pale blue premixed flame had already formed within the cylinder, and the ignition delay of the second diesel injection was influenced by the presence of this premixed flame. The ignition delay of the diesel droplets from the second injection decreases gradually as SOI1 advances. Compared to the single injection strategy, the split injection strategy forms smaller high-temperature regions during the combustion process, thereby displaying a discernible trend toward reducing NOx emissions. Since the energy contribution of the second diesel injection is only 2%, the turbulence and diffusion flames formed by the second diesel injection have a relatively low impact on the propagation of the methane premixed flame. The flame front for single injection strategy is closer to the thickened flames region, suggesting a thicker flame surface due to the concentrated distribution of diesel. [ABSTRACT FROM AUTHOR]

Deep learning has emerged as a powerful tool to model complicated relationships between inputs and outputs in manufacturing systems. Existing deep learning approaches in manufacturing are often used to directly predict the Variables of Interest (VoI) such as the system status from a set of sensor measurements by supervised learning. However, in various complex manufacturing systems, components are operated under multiple modes that are not well known beforehand. The mapping of the VoI from sensor measurements highly depends on the mode information given that sensor measurements under different operation modes usually present different patterns. Therefore, predicting the VoI under multiple operation modes given sensor measurements is urgently necessary. This study develops a novel deep learning method for multimodal regression and mode recognition to predict the VoI under multiple modes and recognize the specific mode of a component from its sensor measurements. Specifically, we establish a deep neural network (DNN)-based regression- and classification-integrated framework. For model training, our innovative idea is to develop an Expectation–Maximum (EM)-based backpropagation algorithm, where the modes of components are set as latent variables, given that the mode information cannot be provided. Numerical experiments and a case study of degraded gas turbine engines are presented to validate the proposed model performance. [ABSTRACT FROM AUTHOR]

Tandem bladed axial flow compressor concept has immense potential for increasing the stage loading over conventional stages. This infers significant improvement in gas turbine engine operational economics and performance. However, implementation of tandem configuration invites additional three dimensionalities in the flow field. This complicates the design process limiting the realization of the tandem bladed rotor concept. The present study addresses the strategies for development of a low-speed axial compressor design implementing tandem bladed rotor and single stator. Both the rotor and stator flow mechanisms have been investigated in detail using steady state simulations. A highly loaded tandem bladed rotor is followed by single bladed stator which handles the highly swirled flow. The single blade configuration of stator results in higher diffusion factor which is more susceptible to the flow separation. Moreover, a dual wake structure evolves through the rotor passage due to highly loaded individual blades. The stage design follows an unconventional approach of tandem rotor-single stator over the reported tandem rotor-tandem stator or only tandem bladed stator configuration. The aerodynamic match between the tandem bladed rotor and stator has been of critical importance in development of this design. The rotor has been designed for highest possible energization of flow by fine tuning the variation of tandem nozzle geometry throughout the span to complement the intended loading profile. The stator is aimed at letting the flow pass through with a chordwise varying diffusion profile. The novelty of the work lies in discussion of tandem rotor and single bladed stator flow physics altogether highlighting the interdependence of decision-making process for both. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The methods of increasing the efficiency of internal combustion engines through heat utilization are examined. A proposed classification of heat utilization systems for mobile energy vehicles is presented. External utilization harnesses the heat generated by a diesel engine to fulfill the needs of consumers not directly related to the engine, such as interior heating and air conditioning systems. Internal recycling focuses on enhancing the power, environmental performance, and economic performance of an engine and its related systems. Various heat utilization schemes are compared. For the economic conditions of the European Union (EU), a turbocompounding diesel engine is acceptable if its agricultural tractor rated power is more than 275 kW and its combine harvester rated power is more than 310 kW. Steam injection into the combustion chamber is utilized to improve the technical and economic performance of gas turbine engines. This technology is also produced in Ukraine and is proposed for use in internal combustion engines. It is suggested to inject water vapor into a turbocharger turbine. This approach reduces the number of components in the heat recovery system, thereby lowering its cost. A recycling chiller can be employed to cool the air after it passes through the air cleaner, enhance the efficiency of the air cooler, and improve the performance of the thermoelectric generators. This device is particularly effective at relatively high air temperatures and can be recommended for agricultural machinery that operates in such conditions, such as combines. With the application of this new technology, it is possible to increase the power of diesel engines by 15...20% and reduce fuel consumption by up to 14%. Further research will focus on substantiating the parameters of recycling systems for different classes of vehicles. Developing a methodology to justify the effective application of heat utilization systems in agricultural mobile energy vehicles is advisable. [ABSTRACT FROM AUTHOR]

The changes in demand disruptions and credit prices in the new energy vehicle (NEV) market under the dual credit policy pose challenges to the decision optimization of vehicle manufacturers and battery manufacturers in different production modes. To address this issue, based on the characteristics of the dual credit policy, this paper constructs a Stackelberg game model for both a single production mode that only produces NEV and a hybrid production mode that produces both NEVs and internal combustion engine vehicles (ICEVs), and solve for the optimal battery research and development (R&D) levels and pricing decisions of enterprises. On the basis of indepth analysis of the results, we further validate the results using numerical examples. The research results indicate that both demand disruptions and credit prices have a positive correlation with the sales prices of NEVs, battery prices, and battery R&D levels; Interestingly, demand disruptions and credit prices also have a positive correlation with the sales prices of ICEVs in a hybrid production mode; The decisions and profits of enterprises in a single production mode have higher robustness compared to a hybrid production mode; Government departments should actively continue to implement the dual credit policy and increase the credit price, which not only benefits the development of the NEV industry, but also contributes to the global environmental protection cause. [ABSTRACT FROM AUTHOR]

With emissions regulations becoming increasingly restrictive and the advent of real driving emissions limits, control of engine-out NOx emissions remains an important research topic for diesel engines. Progress in experimental engine development and computational modelling has led to the generation of a large amount of high-fidelity emissions and in-cylinder data, making it attractive to use data-driven emissions prediction and control models. While pure data-driven methods have shown robustness in NOx prediction during steady-state engine operation, deficiencies are found under transient operation and at engine conditions far outside the training range. Therefore, physics-based, mean value models that capture cyclic-level changes in in-cylinder thermo-chemical properties appear as an attractive option for transient NOx emissions modelling. Previous experimental studies have highlighted the existence of a very strong correlation between peak cylinder pressure and cyclic NOx emissions. In this study, a cyclic peak pressure-based semi-empirical NOx prediction model is developed. The model is calibrated using high-speed NO and NO2 emissions measurements during transient engine operation and then tested under different transient operating conditions. The transient performance of the physical model is compared to that of a previously developed data-driven (artificial neural network) model, and is found to be superior, with a better dynamic response and low (<10%) errors. The results shown in this study are encouraging for the use of such models as virtual sensors for real-time emissions monitoring and as complimentary models for future physics-guided neural network development. [ABSTRACT FROM AUTHOR]

Considering the strict regulations on the transport sector emissions, predictive models for engine emissions are essential tools to optimize high-efficient low-emission internal combustion engines (ICE) for vehicles. This aspect is of major importance, especially for developing new combustion concepts (e.g. lean, pre-chamber) or using alternative fuels. Among the gaseous emissions from spark-ignition (SI) engines, unburned hydrocarbons (uHC) are the most challenging species to model due to the complexity of the formation mechanisms. Phenomenological models are successfully used in these cases to predict emissions with a reduced computational effort. In this work, uHC phenomenological model approaches by the authors are further developed to improve the model predictivity for multiple variations including engine design, engine operating parameters, as well as different fuels and ignition methods. The model accounts for uHC contributions from piston top-land crevice, wall flame quenching, oil film fuel adsorption/desorption and features a tabulated-chemistry approach to describe uHC post-oxidation. With the support of 3D-CFD simulations, multiple novel modelling assumptions are developed and verified. The model is validated against an extensive measurement database obtained with two small-bore single-cylinder engines (SCE) fuelled with gasoline-like fuel, one with SI and one with pre-chamber, as well as against data from two different ultra-lean large-bore engines fuelled with natural gas (one equipped with a pre-chamber and one dual-fuel with a diesel pilot). The model correctly predicts the trends and absolute values of uHC emissions for all the operating conditions and the engines with an accuracy on average of 11.4%. The results demonstrate the general applicability of the model to different engine designs, the correct description of the main mechanisms contributing to fuel partial oxidation, and the potential to be extended to predict unburned fuel emissions with other fuels. [ABSTRACT FROM AUTHOR]

Titanium alloy, Ti–6Al–2.2Mo–1.4Cr–0.4Fe–0.3Si (BT3-1), is a two phase α + β alloy developed for applications in rocket engines, gas turbine engines, and aircraft frames for service up to a temperature of 450 °C. The hot workability of this alloy has been studied through isothermal hot compression testing in the temperature and strain rate (ε ˙) range of 800 °C to 1000 °C and 10−3 to 10 s−1, respectively, in a thermomechanical simulator. Processing maps using dynamic material model has been generated and different regions of the map were correlated with microstructural observations. The flow stress data were fitted in Arrhenius strain-compensated model and constitutive equations were developed. Optical microstructures revealed elongated grains, kinking of α phase, flow localisation, and adiabatic shear bands at lower temperatures. Super-plasticity was found to be operative at low temperature of 850 °C and ε ˙ 10−3 s−1, whereas dynamic recrystallization (DRX) was dominating at high temperatures of 950 °C to 1000 °C and ε ˙ of 10−3 s−1. Finite element analysis showed the flow localization in the unstable regions of processing map. Enhanced hot workability was achieved above 950°C in the ε ˙ of 10−2−10−3 s−1 due to initiation of DRX in view of an increase in the β phase fraction. [ABSTRACT FROM AUTHOR]

Overcoming the use of conventional internal combustion engines for future transportation is mandatory to achieve sustainability. In this regard, hybrid electric vehicles comprising hydrogen fuel cells with Li-ion battery storage are gaining more attention. The paper proposes a robust approach for economic power-sharing between these sources. A predictive speed control strategy is realized to improve the vehicle's overall operation compared to conventional proportional–integral–derivative controller and tested for various standardized driving cycles. Additionally, a comprehensive techno-economic analysis using total cost of ownership is performed. Results suggest that hybrid vehicles with fuel cells and batteries are more economical with costs($) of 5. 81 e 04 , 2. 17 e 04 , and 2. 04 e 05 , for transient, modal, and manual driving cycles, respectively compared with internal combustion engines and batteries having 6. 23 e 04 , 3. 21 e 04 , and 2. 54 e 05. Furthermore, for evaluating the performance of the proposed predictive controller in terms of error minimization, various performance indices are obtained, compared, and tested using a hardware-in-loop platform. • Predictive control-based optimal power management approach. • Economic benefits through hydrogen fuel cells (HFCs) as an auxiliary energy source. • The controller's performance investigation through performance indices (PIs). • Validation using simulation and Hardware-in-loop results. • Techno-economic analysis for full lifetime use of the HEV. [ABSTRACT FROM AUTHOR]

Argon Power Cycle (APC) combustion engine has a high efficiency, zero carbon emissions, and zero pollutant emissions, rendering it a promising way for achieving zero or carbon neutrality within the realm of internal combustion engine (ICE) technology. Previous studies have shown that while APCs significantly improve the thermal efficiency of ICEs, they also face serious knock problems due to their high temperatures and pressures, especially when hydrogen is used as a fuel. In this study, the anti-knocking characteristics of hydrogen, methane, carbon monoxide, and ammonia were first investigated in APC through thermodynamic calculations by Ignition Delay Time. Then, based on testbench experiments, hydrogen and methane fuels were selected to further investigate the effect of different fuel anti-knocking characteristics on the indicated thermal efficiency and power of APC combustion engine. Test results showed that when using hydrogen, the APC ICE exhibited a pronounced knock tendency, and the test engine could not operate stably when the excess oxygen ratio <2.1 at compression ratio = 9.6. The CA50 of the maximum efficiency point was delayed in APC than in air for both hydrogen and methane, specially H 2 has an obvious lag at about 5–15 ° CA. In comparison, when using methane, the combustion control of engine is easier, and the peak indicated thermal efficiency 59% and the peak indicated mean effective pressure 0.92 MPa are higher than 54.3% and 0.60 MPa of using hydrogen. The use of hydrogen still needs an anti-knocking strategy while an extra carbon capture device is necessary to ensure a closed argon cycle if methane is employed. • Ignition Delay Time calculated by simulation presents a good judgement to evaluate knocking-resistance for gaseous fuel. • Evaluating the knock in the APC ICE employing the CA50 of max efficiency verifies that CH 4 has a better knocking-resistance. • Due to better knock resistance, CH 4 -fueled APC ICE achieved higher thermal efficiency +4.7% and IMEP +0.32MPa than H 2. [ABSTRACT FROM AUTHOR]

Hydrogen mobility embodies a promising solution to address the challenges posed by traditional fossil fuel-based vehicles. The use of hydrogen in small heavy-duty road vehicles based on internal combustion engines (ICEs) may be appealing for two fundamental reasons: Direct electrification seems less promising in heavy-duty transport systems, and fuel cell-based hydrogen vehicle implementation may not proceed at the expected pace due to higher investment costs compared to ICEs. On the other hand, hydrogen combustion is gaining attractiveness and relies on robust and cheap technologies, but it is not the only renewable solution. In this framework, this work presents a methodology to assess the Well-to-Wheel primary energy consumption and CO2 emissions of small heavy-duty vehicles. The methodology is applied in a real case study, namely a passenger coach traveling on a 100 km mission in non-optimized conditions. Therefore, the suitability of hydrogen is compared with standard diesel and other alternative diesel-type fuels (biodiesel and synthetic diesel types). Hydrogen shows competitivity with standard diesel from the point of view of CO2 emission reduction (−29%) while it hides a higher primary energy consumption (+40%) based on the current power-to-hydrogen efficiency declared by electrolyzer manufacturers. Nonetheless, HVO brings the highest benefits both from the point of view of primary energy consumption and emission reduction, namely −35% and 464–634 kgCO2/100km avoided compared to hydrogen. Moreover, the availability of HVO—like other biofuels—does not depend on carbon from CO2 capture and sequestration systems. [ABSTRACT FROM AUTHOR]

The growing demand to reduce emissions of pollutants and CO2 from internal combustion engines has led to a critical need for the development of ultra-lean burn engines that can maintain combustion stability while mitigating the risk of knock. One of the most effective techniques is the pre-chamber spark-ignition (PCSI) system, where the primary combustion within the cylinder is initiated by high-energy reactive gas jets generated by pilot combustion in the pre-chamber. Due to the complex physical and chemical processes involved in PCSI systems, performing 3D CFD simulations is crucial for in-depth analysis and achieving optimal design parameters. Moreover, combining a detailed CFDs model with a calibrated 0D/1D model is expected to provide a wealth of new insights that are difficult to gather through experimental methods alone, making it an indispensable tool for improving the understanding and optimization of these advanced engine systems. In this context, numerous previous studies have utilized CFD models to optimize key design parameters, including the geometric configuration of the pre-chamber, and to study combustion characteristics under various operating conditions in PCSI engines. Recent studies indicate that several advanced models designed for conventional spark-ignition (SI) engines may not accurately predict performance under the demanding conditions of Turbulent Jet Ignition (TJI) systems, particularly when operating in lean mixtures and environments with strong turbulence–chemistry interactions. This review highlights the pivotal role of Computational Fluid Dynamics (CFDs) in optimizing the design of pre-chamber spark-ignition (PCSI) engines. It explores key case studies and examines both the advantages and challenges of utilizing CFDs, not only as a predictive tool but also as a critical component in the design process for improving PCSI engine performance. [ABSTRACT FROM AUTHOR]

The use of renewable fuels in place of fossil fuels in internal combustion engines is regarded as a viable method for achieving zero-impact-emission powertrains. However, to achieve the best performance with these fuels, these engines require further optimization, which is achieved through new combustion strategies and the use of advanced ignition systems such as prechambers. Since simulations greatly accelerate this development, accurate simulation models are needed to accurately predict the combustion phenomenon, which requires a deep understanding of the ignition phenomenon as it significantly affects combustion. This work presents a comprehensive experimental methodology to study sparks under engine conditions, providing quantitative data to improve and validate ignition simulation models. The goal was to determine the volume generated by sparks under engine conditions that can initiate combustion and use this information to improve simulation results to match the experimental results. The visible sparks were observed with high-speed cameras to understand their time-resolved evolution and interaction with the flow. The heat transfer from the plasma was also visualized using a modified Background-Oriented Schlieren technique. The information gained from the experimental observations was used to improve an ignition simulation model. Since the velocity of the plasma was found to be slower than the surrounding flow, a user-defined parameter was included to calibrate the velocity of the simulated plasma particles. This parameter was calibrated to match the simulated spark length to the experimental spark length. In addition, since the previous simulation model did not take the heat transfer from the plasma into account, the simulated plasma particles were coupled to have heat transfer to the surroundings. Based on a comparison of the simulation results with the experimental results, the improved approach was found to provide a better physical representation of the spark ignition phenomenon. [ABSTRACT FROM AUTHOR]

In this study, a series of carrier-phase direct numerical simulations are conducted on spherical expanding premixed hydrogen/air flames with liquid water addition. An Eulerian–Lagrangian approach with two-way coupling is employed to describe the liquid–gas interaction. The impacts of preferential diffusion, the equivalence ratio, water loading, and the initial diameter of the water droplets are examined and analyzed in terms of flame evolution. It is observed that liquid water has the potential to influence flame propagation characteristics by reducing the total burning rate, flame area, and burning rate per unit area, attributed to flame cooling effects. However, these effects become discernible only under conditions where water evaporation is sufficiently intense. For the conditions investigated, the influence of preferential diffusion on flame evolution is found to be more significant than the interaction with liquid water. The results suggest that due to the slow evaporation rate of water, which is a result of its high latent heat of evaporation, the water droplets do not disturb the initial flame kernel growth significantly. This has implications for water injection concepts in internal combustion engines and for explosion mitigation. [ABSTRACT FROM AUTHOR]

The organic Rankine cycle (ORC) system is an important technology for recovering energy from the waste heat of internal combustion engines, which is of significant importance for the improvement of fuel utilization. This study analyses the performance of vehicle ORC systems and proposes a rapid optimization method for enhancing vehicle ORC performance. This study constructed a numerical simulation model of an internal combustion engine-ORC waste heat recovery system based on GT-Suite software v2016. The impact of key operating parameters on the performance of two organic Rankine cycles: the simple organic Rankine cycle (SORC) and the recuperative organic Rankine cycle (RORC) was investigated. In order to facilitate real-time prediction and optimization of system performance, a data-driven rapid prediction model of the performance of the waste heat recovery system was constructed based on an artificial neural network. Meanwhile, the NSGA-II multi-objective algorithm was used to investigate the competitive relationship between different performance objective functions. Furthermore, the optimal operating parameters of the system were determined by utilizing the TOPSIS method. The results demonstrate that the highest thermal efficiencies of the SORC and RORC are 6.21% and 8.61%, respectively, the highest power outputs per unit heat transfer area (POPAs) are 6.98 kW/m2 and 8.99 kW/m2, respectively, the lowest unit electricity production costs (EPC) are 7.22 × 10−2 USD/kWh and 3.15 × 10−2 USD/kWh, respectively, and the lowest CO2 emissions are 2.85 ton CO2,eq and 3.11 ton CO2,eq, respectively. The optimization results show that the RORC exhibits superior thermodynamic and economic performance in comparison to the SORC, yet inferior environmental performance. [ABSTRACT FROM AUTHOR]

Hydrogen energy has been under close scrutiny by countries around the world. At present, the main technologies for utilizing hydrogen energy in transport power systems are hydrogen internal combustion engine (HICE) and proton exchange membrane fuel cell (PEMFC). Since both of them generate a large amount of waste heat, and waste heat recovery technology is one of the most promising means of utilizing waste heat to improve efficiency, this paper makes a comprehensive comparison of the two technologies in composite waste heat recovery (WHR) system in terms of modeled maximum efficiency, full operating condition efficiency and future predicted maximum efficiency. Based on the thermal efficiency analysis, the advantages, disadvantages, and development prospects of the two technologies in composite the WHR system are reevaluated. The results demonstrate that the efficiency of the HICE and PEMFC can be improved by 6.83% and 2.81%, with the use of WHR system, respectively. Under the full range of operating conditions, the HICE-WHR composite system has obvious efficiency advantage in middle-high load working condition, but PEMFC-WHR composite system has obvious efficiency advantage in low load working condition. Both of them will be very competitive and potential technology routes of hydrogen energy utilization for land transportation. [ABSTRACT FROM AUTHOR]

Internal combustion engine fueled by carbon-free hydrogen (H2-ICE) offers a promising alternative for sustainable transportation. Herein, we report a facile and universal strategy through the physical mixing of Pt catalyst with zeolites to significantly improve the catalytic performance in the selective catalytic reduction of nitrogen oxides (NOx) with H2 (H2-SCR), a process aiming at NOx removal from H2-ICE. Via the physical mixing of Pt/TiO2 with Y zeolite (Pt/TiO2 + Y), a remarkable enhancement of NOx reduction activity and N2 selectivity was simultaneously achieved. The incorporation of Y zeolite effectively captured the in-situ generated water, fostering a water-rich environment surrounding the Pt active sites. This environment weakened the NO adsorption while concurrently promoting the H2 activation, leading to the strikingly elevated H2-SCR activity and N2 selectivity on Pt/TiO2 + Y catalyst. This study provides a unique, easy and sustainable physical mixing approach to achieve proficient heterogeneous catalysis for environmental applications. The integration of Pt-oxide catalyst systems with zeolites demonstrates considerable promise for reducing nitrogen oxide emissions at low temperatures from fossil-fuel or hydrogen-powered internal combustion engines. [ABSTRACT FROM AUTHOR]

To achieve sustainable transportation, ammonia (NH 3) and hydrogen (H 2) should be applied in internal combustion engines. The adoption of turbulent jet ignition (TJI) can improve ignition and combustion stability. The present study aims to explore the combustion characteristics of NH 3 /H 2 /air adopting TJI, and the effect of nitrogen (N 2) dilution on factors such as ignition mechanism and flame propagation process was analyzed. The results indicate that N 2 dilution worsens the combustion of NH 3 /H 2 /air. When the H 2 volume fraction is 50%, a dilution ratio of 30% can increase the ignition delay and combustion duration by 3–6 times. With the increase of the dilution ratio, sensitivities of ignition delay and combustion duration to dilution ratio are enhanced in both passive TJI and active TJI modes. Compared to passive TJI, the injection of auxiliary gas in active TJI mode reduces the sensitivity of jet velocity to dilution, which can accelerate the early stage of flame development. However, the high turbulence intensity provided by active TJI makes the ignition position closer to the bottom and causes an extended final stage of combustion. For ultra-low reactivity mixtures, the active TJI with the scavenging system can provide sufficient ignition energy, but ignition occurs after prolonged accumulation of heat and radicals, as well as dissipation of turbulence. • Effects of N 2 dilution on NH 3 /H 2 /air combustion with TJI is studied. • H 2 -assisted TJI reduces the sensitivity of ignition performance to dilution. • High-speed jet suppresses flame propagation near the orifice in active TJI mode. • Scavenging can improve the flammability limit for N 2 diluted NH 3 /H 2. • Weak flame may occur in the early combustion for low reactivity mixture. [ABSTRACT FROM AUTHOR]

To avoid increasing the dilution gas to achieve higher temperatures for rapid compression machines (RCM) at the end of compression, this study introduced an oil-bath heating system designed to precisely improve the initial temperature of the mixture, thereby enabling ammonia-hydrogen ignition at practical fuel concentrations for internal combustion engines (ICEs). Using this oil-bath heated RCM, the ignition delay times (IDTs) of ammonia-hydrogen under conditions relevant to ICEs were measured. The ammonia-hydrogen combustion mechanism proposed by Stagni et al. (10.1016/j.proci.2022.08.024) was then validated against these measured IDTs and subsequently optimized. Guided by a comprehensive review of the existing literature on ammonia-hydrogen chemistry, the optimization involved updating 42 reaction rate coefficients and adding 9 new reactions. The optimized mechanism, comprising 31 species and 214 reactions, demonstrated accurate predictions of ignition delay time, laminar flame speed, and species mole fractions across a wide range of experimental setups and conditions for ammonia-hydrogen, confirming the mechanism's robust performance and its suitability for high-precision simulations in ammonia-hydrogen ICE applications. • An oil-bath heating system was developed to elevate the mixture temperatures of an RCM. • The NH 3 –H 2 ignition delay times (IDTs) at engine relevant conditions were measured. • An NH 3 –H 2 kinetic model was constructed with reliable reaction rate constants. • The model well predicts the NH 3 –H 2 IDTs, laminar flame speed, and species mole fractions. [ABSTRACT FROM AUTHOR]

One of the primary concerns with fuel combustion in internal combustion engines is the significant quantity of energy that is dissipated as waste heat, which leads to thermal pollution and reduced engine efficiency. To address this issue, a new integrated system incorporating a natural gas fueled homogeneous charge compression ignition (HCCI) engine for different hydrogen fractions (0%–20%) in fuel blends and its exhaust heat is recovered to drive the NH 3 –H 2 O based absorption refrigeration cycle (ARC) and process heat exchanger has been developed, which encompasses the generation of electricity, heating, and cooling. A comprehensive energy-exergy model was built and the impact of some key operating variables on the performance of combined system are investigated. Simulation of the proposed system was performed using Engineering Equation Solver (EES) software and REFPROP toolbox library data. The energy and exergy efficiencies of HCCI engine resulted in an increase from 45.26% to 55.45% and from 41.15% to 46.14%, whereas the combined system efficiencies were increased by 15.90% and 10.13% when hydrogen addition is promoted from 0% to 20%. Utilization of 10% hydrogen resulted in energy efficiency of 49.57% for electrical, 11.89% for cooling, and 4.51% for heating. Illustration of exergy flow diagram identified HCCI engine (118.29 kW, 32.11%) as the most fuel exergy destructive component, followed by ARC cycle (30.86 kW, 8.37%), catalytic converter (27.24 kW, 7.39%) and process heat exchanger (11.103 kW, 3.01%). Impressive exergetic results from the system include a power exergy of 158.91 kW (43.14%), heating exergy 10.697 kW (2.90%), and cooling exergy 3.92 kW (1.06%). • H 2 enriched natural gas fueled HCCI engine based trigeneration system was developed. • HCCI engine's exhaust waste heat was harnessed through the ARC cycle and PHE. • A single effect NH 3 –H 2 O absorption chiller was employed for cold production. • Energy and exergy-based assessment was carried out to analyze the proposed system. • HCCI engine (32.11%) were identified as the primary exergy destructive components. [ABSTRACT FROM AUTHOR]

In this study we assess periodicities in nitrogen dioxide levels at a location in Los Angeles using a novel Variable Bandpass Periodic Block Bootstrap (VBPBB) method resulting in confidence interval bands for the periodic mean. Nitrogen dioxide (NO2) is an air pollutant primarily produced by the combustion of fossil fuels by power plants and vehicles with internal combustion engines which has been linked with a variety of adverse health outcomes including dementia, breast cancer, decreased cognitive function, increased susceptibility to Covid-19, cardiovascular and respiratory mortality. Previous analysis methods such as block bootstrapping can obscure periodically correlated patterns in time series. The sampling destroys the correlation observed in the data for patterns of different periods, such as the daily, weekly and yearly patterns of nitrogen dioxide levels we wish to investigate. We use the VBPBB method to isolate significant periodicities using a band pass filter before bootstrapping so that the correlations between the data are preserved. Confidence interval bands for VBPBB are compared against existing block bootstrapping. The resulting narrower confidence interval bands created by VBPBB show a significant annual fluctuation in nitrogen dioxide levels while the existing methods do not show it as clearly. Better characterization of pollution patterns will aid in pollution reduction efforts by allowing us to pinpoint times of highest risk and direct mitigation efforts where they will have the greatest impact. This technique exhibits potential for future applications to other areas of environmental and health interest and concern. [ABSTRACT FROM AUTHOR]